In-vitro diagnostics (IVD) allows labs to assist in the diagnosis of disease based on assays performed on patient fluid samples. IVD includes various types of analytic tests and assays related to patient diagnosis and therapy that can be performed by analysis of a liquid sample taken from a patient's bodily fluids, or abscesses. These assays are typically conducted with automated clinical chemistry analyzers (“analyzers”) onto which fluid containers, such as tubes or vials containing patient samples, have been loaded. The analyzer extracts a liquid sample from the vial and combines the sample with various reagents in special reaction cuvettes or tubes (referred to generally as reaction vessels). In some conventional systems, a modular approach is used for analyzers. A lab automation system can shuttle samples between one sample processing module (module) and another module. Modules may include one or more stations, including sample handling stations and testing stations (e.g., a unit that can specialize in certain types of assays or can otherwise provide testing services to the larger analyzer), which may include immunoassay (IA) and clinical chemistry (CC) stations. Some traditional IVD automation track systems comprise systems that are designed to transport samples from one fully independent module to another standalone module. This allows different types of tests to be specialized in two different stations or allows two redundant stations to be linked to increase the volume of sample throughput available.
These lab automation systems, however, often use individual pucks to transport samples within an analyzer, utilizing a single track. While this track can have branches to direct selected carriers to stations within the analyzer, these systems still rely on main track, which may be a unidirectional loop or bidirectional linear track. While this arrangement may be suitable for smaller laboratories, relying on a single track to transport thousands of samples per hour can limit scalability of the system. As the number of samples per hour being processed by the system goes up, the number of samples traversing the automation track also increases. Similarly, in prior art systems, the size of the track can also increase, causing the larger number of samples to also spend more time on the automation tracks. This can cause the automation track to become a performance bottleneck.
Some prior art systems have mitigated this issue by using carriers that hold more than one sample as the carriers traverse the automation system. While this can reduce the number of carriers on the track, all samples in each multi-sample carrier must go to all locations within the system where a single sample might need to go, which can increase the amount of time a carrier spends on the track. Meanwhile, the track that must be traversed still grows with the number of stations provided. Scalability is still limited. Accordingly, it is desirable to have an automation system that allows greater scalability as a lab grows.